Previous generation fitness tracking devices generally only enabled a user to identify their heart rate during an exercise session or other activity. More modern fitness tracking devices now add functionality that monitor and track a user's fitness level, for example, by counting the user's steps, estimating the total calories burned, miles run, etc., and/or by estimating the user's heart rate variability and other biometric data. Nevertheless, currently available fitness monitoring devices do not provide a user with a precise measure of exertion during and throughout a given exercise session, and further do not provide a precise exertion recommendation for a future exercise session based on prior measures. In particular, currently available devices do not provide a personalized and precise exertion recommendation for an upcoming exercise session, as a measure of the user's prior exertion measures, response profile (i.e. performance capacity) measures, and the like.
Because each person has unique physical characteristics and capabilities, the effort required to perform a given activity or task—and the intensity with which the task may be performed—may differ between individuals. For example, a person with short legs may need to exert more effort to run a mile in six minutes than a person with much longer legs, all else being equal. Moreover, each person has unique recovery characteristics that may also change with time—whether in the short term or long term. For example (demonstrating long term changes), in running a marathon a middle-aged person may find that with each mile they experience more fatigue (i.e. slower recovery) than they did when they ran the same marathon as a teenager. In another example (demonstrating short term changes), a weight-lifter wishing to perform 20 reps on a bench press will need to exert more effort to lift the barbell the twentieth time than she did for the nineteenth time; or in other words recovery will gradually slow throughout the set of 20 reps (and therefore greater effort will be required with each consecutive rep) because of the effort already exerted in each previous rep. In other words, the effort required to perform a given activity will differ from one moment to the next for particular individuals—even within the same exercise session—depending on what they have been doing up to that point. Finally, the effort required to perform a given activity may differ depending on how quickly the activity must be performed. For example, a person must exert more energy (i.e. greater intensity) to run a mile in six minutes than to run a mile in ten minutes, and the impact of each scenario will differ accordingly.
In view of the foregoing incongruities, quantifying and providing a precise and personalized measure of exertion, as well as a precise and personalized measure of the user's response profile, can be of great value to athletes seeking to modify, track, or gauge the effectiveness of their training regimen, project the impact of a particular activity on their physical condition at a given moment after a previously performed activity, or to make any other such exertion based assessment. Furthermore, conventional devices do not provide a precise and personalized exertion recommendation to user's for a future exercise session (or other activity or time interval) based on the user's prior exertion measures and/or prior response profile measures. Because currently available devices do not provide such a precise such measures, it can be difficult for a user to meaningfully assess the impact that a particular activity has had, is currently having, or will have on their body (e.g. energy level, capacity, stamina, etc.); and be even more difficult to intelligently evaluate how to approach an anticipated exercise session to achieve their desired goals.